Project performance management and control method, device and equipment, product and storage medium

Abstract

The invention relates to a project performance management and control method, device and equipment, a product and a storage medium. The method comprises the following steps: constructing a performance management and control model of a target project; the performance management and control model is provided with performance nodes set based on a target project, multiple stages of intermediate nodes set stage by stage from the performance nodes, and multiple child nodes set from the tail end intermediate node; respectively determining a weight coefficient of each node at the same level in the corresponding upper-level intermediate node or performance node; and obtaining the performance score of the child node, and determining the performance score of the intermediate node and the total performance score of the performance node step by step based on the performance score of the child node, the weight coefficient of the child node and the weight coefficient of the intermediate node, so as to perform performance management and control on the target project based on the total performance score. Compared with the prior art, the resource allocation and scheduling can be effectively optimized, and unnecessary delay is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of power plant operation and maintenance evaluation, and in particular to a project performance management method, device, equipment, product and storage medium. Background Art

[0002] Pumped storage power station is a type of energy storage power station. It has the characteristics of large scale, long life and high efficiency. It is a mature and widely used physical energy storage technology. The construction of pumped storage power station can not only effectively balance the supply and demand of electricity, but also improve the stability and reliability of the power grid. It is an important part of building a smart grid.

[0003] The project management of pumped storage power stations is significantly complex in terms of scale, organization, technology, environment, etc. In order to evaluate the performance of each project, a scientific performance management system needs to be established. By performing performance management on engineering projects, resource allocation and scheduling can be effectively optimized to reduce unnecessary delays.

[0004] However, existing performance management methods are usually calculated based on indicators in a single group or system, resulting in low accuracy of performance scores and failure to provide managers with a reliable basis for decision-making. Summary of the invention

[0005] Based on this, it is necessary to provide a performance management method, device, equipment, product and storage medium for projects that can output accurate, objective and scientific performance scores in response to the above technical problems.

[0006] In a first aspect, the present application provides a project performance control method, the method comprising:

[0007] Construct a performance control model for the target project; the performance control model has a performance node set based on the target project, a multi-level intermediate node set step by step from the performance node, and a plurality of sub-nodes set from the terminal intermediate node; the intermediate node at least includes a plurality of parallel system nodes and a plurality of parallel element nodes set downward from each system node, each element node is provided with a plurality of parallel sub-nodes, and the sub-nodes are defined as measure nodes, the target project has a project management subsystem divided according to the horizontal dimension of performance control and corresponding one-to-one with the system nodes, each of the management subsystems has a plurality of management elements divided according to project management elements and corresponding one-to-one with the element nodes, and each of the management elements has a plurality of management measures divided according to project management measures and corresponding one-to-one with the measure nodes;

[0008] Determine the weight coefficient of each node at the same level in the corresponding intermediate node or performance node at the previous level; the weight coefficient is used to indicate the importance of each node at each level in the corresponding intermediate node or performance node at the previous level for performance control;

[0009] Obtain the performance score of the child node, determine the performance score of the intermediate node step by step based on the performance score of the child node and the weight coefficient of the child node, and determine the total performance score of the performance node based on the performance score of the intermediate node below the performance node and the weight coefficient corresponding to the intermediate node, so as to perform performance control on the target project based on the total performance score.

[0010] In one embodiment, the step of constructing a performance control model for a target project includes:

[0011] Setting the performance node based on the target project;

[0012] Divide the target project into multiple project management subsystems according to the horizontal dimension of performance control, construct a corresponding system node for each project management subsystem, point the system node to the performance node, and construct a performance network between the system node and the performance node;

[0013] Dividing the project management subsystem into a plurality of performance management elements according to project management elements, constructing a corresponding element node for each performance management element, connecting the element node with a corresponding system node, and constructing a performance network between the element node and the system node;

[0014] Divide the performance management elements into multiple management measures according to project management measures, construct corresponding measure nodes for each management measure, connect the measure nodes with corresponding element nodes, and construct a performance network between the measure nodes and the element nodes;

[0015] Based on the performance network between the nodes, the performance management model is constructed.

[0016] In one embodiment, directing the system node to the performance node and building a performance network between the system node and the performance node includes:

[0017] According to the influence relationship between the system nodes corresponding to each project management subsystem and the performance node, the system node is determined as an ordered node or an unordered node; the unordered node directly affects the performance node, and the ordered node indirectly affects the performance node through the corresponding unordered node;

[0018] Each ordered node is pointed to each unordered node, and each unordered node is pointed to the performance node, so as to construct a performance network between the system node and the performance node.

[0019] In one embodiment, the step of respectively determining the weight coefficient of each node at the same level in the corresponding intermediate node or performance node at the previous level includes:

[0020] Determine a first weight coefficient of the importance of each measure node corresponding to the same element node in the corresponding element node according to the preset importance of each measure node relative to the corresponding element node;

[0021] Determining a second weight coefficient of importance of each element node corresponding to the same system node in the corresponding system node according to the preset importance of each element node relative to the corresponding system node;

[0022] Determining a third weight coefficient of the importance of each unordered node corresponding to the performance node in the performance node according to the preset importance of each unordered node relative to the performance node;

[0023] According to the preset importance of each ordered node relative to each unordered node, a fourth weight coefficient of the importance of each ordered node corresponding to the same unordered node in the corresponding unordered node is determined.

[0024] In one embodiment, the first to fourth weight coefficients are determined by the following method:

[0025] Determine a node sequence; the node sequence is an unordered node sequence obtained by sorting the unordered nodes in descending order according to the preset importance in the performance node, an ordered node sequence obtained by sorting the ordered nodes in the corresponding unordered nodes according to the preset importance in the corresponding system node, an element node sequence obtained by sorting the element nodes in descending order according to the preset importance in the corresponding system node, and / or a measure node sequence obtained by sorting the measure nodes in descending order according to the preset importance in the corresponding element node;

[0026] Based on the node sequence, determining a weight coefficient of an nth node in the node sequence; the nth node is the last node in the node sequence;

[0027] Obtaining a relative importance parameter between the nth node and the n-1th node; the relative importance parameter is determined according to the relative importance between two adjacent nodes;

[0028] The weight coefficient of the n-1th node is determined according to the relative importance parameter between the n-th node and the n-1-th node and the weight coefficient of the n-th node, and this cycle is repeated until the weight coefficient of each node is obtained.

[0029] In one embodiment, the obtaining of the performance score of the child node, and determining the performance score of the intermediate node and the total performance score of the performance node step by step based on the performance score of the child node, the weight coefficient of the child node, and the weight coefficient of the intermediate node, include:

[0030] Obtain a first performance score for each measure node, and determine a second performance score for each element node based on the first performance score and the first weight coefficient; determine a third performance score for each system node based on the second performance score and the second weight coefficient; and determine an overall performance score for the performance node based on the third performance score and the third and fourth weight coefficients.

[0031] In a second aspect, the present application also provides a project performance control device, the device comprising:

[0032] A model building module, used to build a performance control model for a target project; the performance control model has a performance node set based on the target project, multiple levels of intermediate nodes set step by step from the performance node, and multiple sub-nodes set from the terminal intermediate node;

[0033] A weight coefficient determination module is used to determine the weight coefficient of each node at the same level in the corresponding intermediate node or performance node at the previous level;

[0034] A performance score output module is used to obtain the performance score of the child node, and determine the performance score of the intermediate node and the total performance score of the performance node step by step based on the performance score of the child node, the weight coefficient of the child node and the weight coefficient of the intermediate node, so as to perform performance management of the target project based on the total performance score.

[0035] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method when executing the computer program.

[0036] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method described above are implemented.

[0037] In a fifth aspect, the present application also provides a computer program product, including a computer program, which implements the steps of the method described above when executed by a processor.

[0038] The performance control method, device, equipment, product and storage medium of the above-mentioned project, when there is a performance control demand for a certain target project, can be achieved by constructing a performance control model for the target project, wherein the performance control model has a performance node set based on the target project, a multi-level intermediate node set step by step from the performance node, and a plurality of sub-nodes set from the terminal intermediate node; then, the weight coefficients of the nodes at the same level in the corresponding upper-level intermediate node or performance node are determined respectively, and the performance scores of the sub-nodes are obtained, and the performance scores of the intermediate nodes and the total performance scores of the performance nodes are determined step by step based on the performance scores of the sub-nodes, the weight coefficients of the sub-nodes and the weight coefficients of the intermediate nodes. The total performance score can reflect the overall performance control of the target project, and after obtaining the total performance score of the target project, the performance control of the target project and the critical path of the project progress can be analyzed according to the level of the total performance score or the performance score corresponding to the nodes at any level, so as to accurately identify the tasks that have the greatest impact on the completion or operation of the project, thereby effectively optimizing resource allocation and scheduling, reducing unnecessary delays, and at the same time, timely improvement measures can be taken for problems existing on the critical path to improve the overall progress and quality of the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 An application environment diagram of a performance control method for a project in an embodiment;

[0041] Figure 2 A schematic diagram of a process flow of a performance control method for a project in one embodiment;

[0042] Figure 3 A schematic diagram of a process for constructing a performance control model for a target project in one embodiment;

[0043] Figure 4 A schematic diagram of the structure of a sequential subtree and a non-sequential subtree in an application example;

[0044] Figure 5 It is a structural diagram of a complex network model in an application example;

[0045] Figure 6 Build a system network diagram for the program subsystem in an application example;

[0046] Figure 7A structural block diagram of a performance control device for a project in an embodiment;

[0047] Figure 8 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0049] The project performance control method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The server 104 constructs a performance control model for the target project. The performance control model uses nodes to represent the elements of each dimension and level in the pumped storage power station, and determines the mutual influence relationship between the nodes by identifying key elements and associated links, and then determines the relative weight of the corresponding nodes. Through the step-by-step transmission of node weights and scores, the performance score of the pumped storage power station is finally obtained, so as to facilitate a comprehensive evaluation of the construction completion or operation level of each power station and improve the control level of the power station. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptops, smart phones, tablets, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, projection devices, etc. Portable wearable devices can be smart watches, smart bracelets, etc. The server 104 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0050] In an exemplary embodiment, Figure 2 As shown in the figure, a performance control method for a project is provided, which is applied to Figure 1 The server in is used as an example. It is understandable that the method can also be applied to a terminal, and can also be applied to a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. The method of this embodiment includes the following steps S201 to S203. Among them:

[0051] Step S201, constructing a performance management and control model for the target project.

[0052] Among them, the performance control model refers to a model constructed based on the performance control or performance evaluation needs of a pumped-storage power station. The performance control model is used to characterize the relationships between various dimensions and levels during the construction or operation of a pumped-storage power station.

[0053] The performance control model has performance nodes set based on target projects, multi-level intermediate nodes set step by step from the performance nodes, and multiple sub-nodes set from the terminal intermediate nodes. The performance nodes correspond to the target projects, the sub-nodes correspond to the specific control means or measures, and the intermediate nodes are located between the performance nodes and the sub-nodes.

[0054] Among them, the intermediate node at least includes a plurality of parallel system nodes and a plurality of parallel element nodes set downward from each system node, each element node is provided with a plurality of parallel sub-nodes, and the sub-nodes are defined as measure nodes. The target project has a project management subsystem divided according to the horizontal dimension of performance control and corresponding to the system nodes one by one, each management subsystem has a plurality of management elements divided according to project management elements and corresponding to the element nodes one by one, and each management element has a plurality of management measures divided according to project management measures and corresponding to the measure nodes one by one.

[0055] Among them, the target project refers to an engineering management project that requires performance control, such as a construction engineering management project, an operation engineering management project, etc. Although this embodiment takes a pumped-storage power station as an example, it should be understood that the aforementioned pumped-storage power station is not a limitation of this embodiment, and this embodiment can also be used for other engineering management projects with performance control requirements.

[0056] Among them, in the entire performance control model, nodes at different levels represent different vertical dimensions. The performance node has the highest level, and usually there is only one performance node, which is associated with the final performance control result. The sub-node has the lowest level, and the number of nodes at the sub-node level is the largest. The sub-node is the starting point of performance control, and is passed forward from the sub-node to the performance node step by step. Depending on the degree of refinement of the performance control target, the intermediate node can have only one layer, multiple layers, or no intermediate node.

[0057] Exemplarily, when there is a demand for performance control for a certain target project, the server responds to the demand and constructs a performance control model for the pumped-storage power station based on the divided dimensions and levels.

[0058] Step S202, respectively determine the weight coefficient of each node at the same level in the corresponding upper-level intermediate node or performance node.

[0059] Among them, the weight coefficient refers to the relative weight of the sub-nodes or lower-level intermediate nodes under the same intermediate node and the intermediate nodes under the performance node in the direct superior node. The weight coefficient is used to indicate the importance of nodes at all levels in the corresponding upper-level intermediate nodes or performance nodes for performance control, that is, it is used to measure the importance of the indicator corresponding to the node in the corresponding upper-level indicator. The larger the weight coefficient, the more important the indicator is, and more consideration needs to be given when conducting performance control. The sum of the weight coefficients between the subordinate nodes under the same node is one.

[0060] Exemplarily, after constructing the performance management and control model, the server determines the weight coefficient of each node at the same level in the corresponding upper-level intermediate node or performance node according to the mutual influence relationship and importance degree between each node.

[0061] Step S203, obtain the performance score of the child node, determine the performance score of the intermediate node step by step based on the performance score of the child node and the weight coefficient of the child node, and determine the total performance score of the performance node based on the performance score of the intermediate node below the performance node and the weight coefficient corresponding to the intermediate node, so as to perform performance management and control on the target project based on the total performance score.

[0062] Among them, performance scoring refers to scoring the importance of the target project from the dimension of the sub-node. Among the sub-nodes belonging to the same intermediate node, the more important or the greater the impact of the intermediate node in performance control, the higher the corresponding score. Usually, the performance score can be determined by empirical methods, such as scoring the performance control dimensions (i.e., the management measures mentioned later) corresponding to each sub-node by professionals in multiple industries and taking the average to obtain the performance score of each sub-node. The average value can be a weighted average (the score of more authoritative or senior personnel is more important, so the weight is greater) or a simple average, etc.; in addition, the performance score can also be obtained by training a scoring model based on a large amount of existing data based on machine learning, neural networks, etc., to increase the objectivity of the preset score. In specific implementation, the performance score can be pre-generated and stored in the data storage system, or it can be generated externally in real time based on the current performance control needs and input into the server.

[0063] Among them, step-by-step determination means that after obtaining the performance score of the intermediate node at the previous level of the child node based on the performance score of the child node and its corresponding weight coefficient, the performance score of the intermediate node at the previous level of the intermediate node is obtained based on the performance score of the intermediate node and its corresponding weight coefficient, and the above process is repeated until the total performance score of the performance node is obtained.

[0064] Exemplarily, the server obtains the performance score of the child node from the data storage system or obtains the performance score input externally; then, the server obtains the weighted performance score of each child node based on the obtained performance score of the child node and the weight coefficient of the corresponding child node, and adds the weighted performance scores of the child nodes belonging to the same intermediate node to obtain the performance score of the intermediate node at the upper level of the child node; then, the server obtains the weighted performance score of each intermediate node on the level based on the performance score of the intermediate node and its corresponding weight coefficient, adds the weighted performance scores of the lower intermediate nodes belonging to the same upper intermediate node (in the case of multiple layers of intermediate nodes) or the performance node (in the case of only one layer of intermediate nodes) to obtain the performance score of the upper intermediate node or the performance node, and determines the performance score of the performance node as the total performance score, so as to perform performance management and control on the target project based on the total performance score.

[0065] In the performance control method of the above-mentioned project, when there is a performance control demand for a certain target project, a performance control model of the target project can be constructed, and the performance control model has a performance node set based on the target project, a multi-level intermediate node set step by step from the performance node, and a plurality of sub-nodes set from the terminal intermediate node; then, the weight coefficients of the nodes at the same level in the corresponding upper-level intermediate node or performance node are determined respectively, and the performance scores of the sub-nodes are obtained, and the performance scores of the intermediate nodes and the total performance scores of the performance nodes are determined step by step based on the performance scores of the sub-nodes, the weight coefficients of the sub-nodes and the weight coefficients of the intermediate nodes. The total performance score can reflect the overall performance control of the target project. Moreover, after obtaining the total performance score of the target project, the performance control of the target project and the critical path of the project progress can be analyzed according to the level of the total performance score or the performance score corresponding to the nodes at any level, so as to accurately identify the tasks that have the greatest impact on the completion or operation of the project, thereby effectively optimizing resource allocation and scheduling, reducing unnecessary delays, and at the same time, for problems existing on the critical path, improvement measures can be taken in time to improve the overall progress and quality of the project.

[0066] In one embodiment, taking a pumped-storage power station as a target project, the dimensions of the target project may be the full-process management dimension, the multi-objective control dimension, and the full-factor security dimension, which are horizontally divided according to the management of the power station. The hierarchy of the pumped-storage power station may be a number of independent project management subsystems divided under each dimension, such as subsystems such as structural decomposition and construction procedures belonging to the full-process management dimension, subsystems such as quality management, safety and health, progress management, and investment management belonging to the multi-objective control dimension, and subsystems such as organization, resources, and technological innovation belonging to the full-factor security dimension. Under each subsystem, different management elements may be further subdivided according to the management objectives, and under each management element, it may be further subdivided into management measures, etc. In this way, a performance control model is formed by dividing the target project for performance control downward step by step.

[0067] Among them, in the above-mentioned target projects, the intermediate nodes at least include multiple parallel system nodes and multiple parallel element nodes set downward from each system node, each element node is set with multiple parallel sub-nodes, and the measure nodes, element nodes, system nodes and performance nodes are connected or pointed step by step from fine to coarse to obtain a performance management and control model.

[0068] like Figure 3 As shown in the figure, a performance control model for the target project is constructed, including:

[0069] Step S301, setting performance nodes based on target projects.

[0070] Step S302, divide the target project into multiple project management subsystems according to the horizontal dimension, and construct a corresponding system node for each project management subsystem, point the system node to the performance node, and build a performance network between the system node and the performance node.

[0071] Among them, the horizontal dimension refers to the performance of the target project in different management areas or functions. This makes it convenient to cluster and compare the management elements and management measures of the same management area or management function to ensure the scientificity and objectivity of performance control.

[0072] Among them, pointing refers to the sequential connection of one node to another node, that is, there is an obvious sequential relationship between the two connected nodes, that is, the nodes perform high-level behaviors in sequence after the low-level node behaviors are completed. In the performance network, "→" is usually used to represent the pointing relationship between two nodes. Among all system nodes, according to the mutual influence relationship between project management subsystems, some system nodes directly point to performance nodes, that is, the project management subsystem corresponding to the system node can directly affect the target project, while some system nodes indirectly point to performance nodes through some other system nodes, that is, the project management subsystem corresponding to the system node indirectly affects the target project by directly affecting other system nodes it points to. In this way, a performance network between system nodes and performance nodes is constructed.

[0073] Exemplarily, based on the above-mentioned performance control requirements, the server divides the target project into multiple project management subsystems according to horizontal dimensions, and constructs corresponding system nodes for each project management subsystem. Subsequently, the server determines the system nodes that can directly affect the performance nodes and the system nodes that indirectly affect the performance nodes, and points the system nodes that can directly affect the performance nodes to the performance nodes, and points the system nodes that indirectly affect the performance nodes to other system nodes that can directly affect the performance nodes, so as to build a performance network between the system nodes and the performance nodes.

[0074] Step S303, divide the project management subsystem into multiple performance management elements according to the project management elements, construct a corresponding element node for each performance management element, connect the element node with the corresponding system node, and construct a performance network between the element node and the system node.

[0075] Among them, project management elements refer to indicators under the project management subsystem that can ensure the successful implementation of the target project and achieve the expected goals. For example, the project decision-making elements, land acquisition and resettlement elements, survey and design elements, bidding and contract management elements, and completion acceptance elements under the construction procedure subsystem reflect the entire process of the construction procedure in the vertical direction to ensure that the target project can be completed and accepted on schedule and meet the design requirements; for example, the personnel elements, material elements, and mechanical equipment elements under the resource subsystem reflect the key resources necessary to achieve efficient and stable operation of the target project to ensure the normal operation of the target project.

[0076] Among them, connection means connecting one node to another node in no order, that is, there is no order between the two connected nodes, and each node jointly guarantees the stable operation of the target project. In the performance network, the connection relationship between two nodes is usually represented by "—". In the performance network, since each element node is virtually connected, in the performance network between the element node and the system node, the connection relationship between the two element nodes is usually represented by an undirected unweighted edge, while between the element node and the system node, an undirected weighted edge is used to represent it.

[0077] Exemplarily, based on the above-mentioned performance control requirements, the server divides each project management subsystem into multiple performance management elements according to project management elements, and constructs a corresponding element node for each performance management element. Subsequently, the element node corresponding to each performance management element is connected to the system node corresponding to the corresponding project management subsystem using an undirected weighted edge to construct a performance network between the element node and the system node.

[0078] Step S304, dividing the performance management elements into multiple management measures according to the project management measures, constructing a corresponding measure node for each management measure, connecting the measure node with the corresponding element node, and constructing a performance network between the measure node and the element node.

[0079] Among them, project management measures refer to specific measures under the project management elements that can ensure the successful implementation of the target project and achieve the expected goals. For example, the formulation and implementation of comprehensive demonstration, feasibility study and site selection under the above-mentioned project decision-making elements; and the formulation and implementation of material quality control, material procurement, material inspection, material stacking, limited material collection and material recycling under the material element.

[0080] Among them, in the performance network, since each measure node is also virtually connected, in the performance network between the measure node and the element node, the connection relationship between the two measure nodes is usually represented by an undirected unweighted edge, while between the measure node and the element node, an undirected weighted edge is used to represent it.

[0081] Exemplarily, based on the above-mentioned performance control requirements, the server divides each performance management element into multiple management measures according to project management measures, and constructs a corresponding measure node for each management measure. Subsequently, the measure node corresponding to each management measure is connected to the element node of the corresponding performance management element using an undirected weighted edge to construct a performance network between the measure node and the element node.

[0082] Step S305: construct a performance management and control model based on the performance network between the nodes.

[0083] In this embodiment, a performance control model is constructed by adopting a method based on graph theory to abstract and model complex systems. During the construction process, the target project is divided in the horizontal and vertical dimensions respectively to determine the mutual influence relationship between various control elements and measures of the target project in each dimension or level, so that in the subsequent calculation and analysis process, the key elements and key links can be accurately and quickly identified, thereby clarifying the focus of safety accident prevention and control of the pumped-storage power station engineering system.

[0084] In one embodiment, the system node is pointed to the performance node, and a performance network is constructed between the system node and the performance node, including:

[0085] According to the influence relationship between the system nodes corresponding to each project management subsystem and the performance nodes, the system nodes are determined as ordered nodes or disordered nodes; each ordered node is pointed to each disordered node, and each disordered node is pointed to the performance node, so as to construct a performance network between the system nodes and the performance nodes.

[0086] Among them, the influence relationship refers to whether the influence of the system node on the performance node is direct or indirect.

[0087] Among them, unordered nodes refer to nodes without a sequence of behaviors in the performance network of system nodes and performance nodes. Unordered nodes directly point to performance nodes to directly affect the performance scores of performance nodes; while ordered nodes refer to nodes with a sequence of behaviors in the performance network of system nodes and performance nodes. Ordered nodes cannot directly point to performance nodes and cannot directly affect the performance scores of performance nodes. They can only indirectly point to performance nodes through corresponding ordered nodes and indirectly affect the performance scores of performance nodes by directly affecting the performance scores of unordered nodes.

[0088] Exemplarily, the server determines the system nodes that directly affect the performance scores of the performance nodes and determines them as unordered nodes based on the influence relationship between the system nodes corresponding to each project management subsystem and the performance nodes, and determines the system nodes that indirectly affect the performance scores of the performance nodes and determines them as ordered nodes; then, the server points each ordered node to each unordered node, and each unordered node to the performance node, to construct a performance network between the system nodes and the performance nodes.

[0089] In this embodiment, since the project management subsystems in the target project jointly affect the operation of the entire project, a performance network integrating series and parallel connections can be formed by directly or indirectly pointing the system nodes to the performance nodes. Failure of any subsystem will cause the target project to stagnate. In this way, all subsystems can be comprehensively considered to build a complete and scientific performance network.

[0090] In one embodiment, determining the weight coefficient of each node at the same level in the corresponding intermediate node or performance node at the previous level includes:

[0091] Determine a first weight coefficient of the importance of each measure node corresponding to the same element node in the corresponding element node according to the preset importance of each measure node relative to the corresponding element node;

[0092] Determining a second weight coefficient of importance of each element node corresponding to the same system node in the corresponding system node according to the preset importance of each element node relative to the corresponding system node;

[0093] Determine a third weight coefficient of the importance of each unordered node corresponding to the performance node in the performance node according to the preset importance of each unordered node relative to the performance node;

[0094] According to the preset importance of each ordered node relative to each unordered node, a fourth weight coefficient of the importance of each ordered node corresponding to the same unordered node in the corresponding unordered node is determined.

[0095] Among them, the preset importance refers to the predetermined degree of importance or influence of each subordinate node relative to its superior node in the performance control process.

[0096] Among them, the first weight coefficient refers to the importance or influence of each measure node under the same element node on the element node in the performance control process. The larger the first weight coefficient, the more important the measure node is in the corresponding element node, and in the performance control process, the management measure corresponding to the measure node has a greater impact on the corresponding performance management element; the sum of the first weight coefficients of each measure node under the same element node is one.

[0097] Among them, the second weight coefficient refers to the importance or influence of each element node under the same system node on the system node in the performance control process. The larger the second weight coefficient, the more important the element node is in the corresponding system node, and in the performance control process, the performance management element corresponding to the element node has a greater impact on the corresponding project management subsystem; the sum of the second weight coefficients of each element node under the same system node is one.

[0098] Among them, the third weight coefficient refers to the importance or influence of each unordered node under the performance node on the performance node in the performance control process. The larger the third weight coefficient, the more important the unordered node is in the performance node, and in the performance control process, the greater the influence of the project management subsystem corresponding to the unordered node on the target project; the sum of the third weight coefficients of each unordered node under the performance node is one.

[0099] Among them, the fourth weight coefficient refers to the importance or influence of each ordered node under the unordered node on the unordered node in the performance control process, and can also be indirectly expressed as the importance or influence of each ordered node on the performance node. The larger the fourth weight coefficient is, the more important the ordered node is in the unordered node, i.e., the performance node, and in the performance control process, the project management subsystem corresponding to the ordered node has a greater influence on the project management subsystem and target project corresponding to the unordered node; the sum of the fourth weight coefficients of each ordered node under the unordered node is one.

[0100] Exemplarily, the server determines, based on the corresponding preset importance, a first weight coefficient of the importance of each measure node corresponding to the same element node in the corresponding element node, a second weight coefficient of the importance of each element node corresponding to the same system node in the corresponding system node, a third weight coefficient of the importance of each unordered node corresponding to the performance node in the performance node, and a fourth weight coefficient of the importance of each ordered node corresponding to the same unordered node in the corresponding unordered node.

[0101] Among them, the preset importance refers to the predetermined degree of importance or influence of each subordinate node relative to its superior node in the performance control process.

[0102] In this embodiment, the weight coefficient of each subordinate node in the corresponding superior node is determined based on the preset importance, and the influence relationship between each node can be embedded in the performance management model to realize the step-by-step transmission of performance scores, thereby facilitating the determination of performance scores of nodes at each level.

[0103] In one embodiment, the first to fourth weight coefficients are determined by the following method:

[0104] Determine a node sequence; based on the node sequence, determine the weight coefficient of the nth node in the node sequence; the nth node is the last node in the node sequence; obtain the relative importance parameter between the nth node and the n-1th node; determine the weight coefficient of the n-1th node based on the relative importance parameter between the nth node and the n-1th node and the weight coefficient of the nth node, and repeat this cycle until the weight coefficient of each node is obtained.

[0105] Among them, the node sequence refers to the sequence obtained by sorting the corresponding system nodes, element nodes and / or measure nodes from large to small according to the preset importance. In the node sequence, the first node is usually more important than the corresponding target project, project management subsystem and / or performance management, and accordingly, its weight coefficient is the largest. Conversely, the last node is less important and its weight coefficient is the smallest. The node sequence of this embodiment is an unordered node sequence obtained by sorting each unordered node from large to small according to the preset importance in the performance node, an ordered node sequence obtained by sorting each ordered node according to the preset importance in the corresponding unordered node, an element node sequence obtained by sorting each element node from large to small according to the preset importance in the corresponding system node, and / or a measure node sequence obtained by sorting each measure node from large to small according to the preset importance in the corresponding element node.

[0106] Among them, since the determination methods of the first to fourth weight systems are the same, this embodiment uses nodes to replace the ordered nodes and unordered nodes, element nodes, and measure nodes in the above-mentioned system nodes, and uses node sequences to replace unordered node sequences, ordered node sequences, element node sequences, and measure node sequences, as well as weight coefficients to replace the first to fourth weight coefficients for illustration. However, it can be understood that in the specific implementation, the node sequences and weight coefficients should be determined accordingly for different types of nodes, that is, for the first weight coefficient, it should be determined by the measure node and its corresponding measure node sequence.

[0107] Among them, the relative importance parameter refers to which node is more important in the performance control process between a certain node and the node in front or behind it in the node sequence, and the parameter obtained by quantitatively assigning the importance of the two nodes according to certain judgment criteria. The relative importance parameter is determined according to the relative importance between two adjacent nodes; for example, the importance between a node A1 and another adjacent node A2 is determined as "A1 is as important as A2", "A1 is slightly more important than A2", "A1 is more important than A2", "A1 is obviously more important than A2" and "A1 is more important than A2", and the importance of each level is quantitatively assigned according to the aforementioned degree to obtain the relative importance parameter of each level, such as 1.0, 1.2, 1.4, 1.6 and 1.8, etc. The aforementioned qualitative and quantitative processes of this embodiment are only used as an example, and can be adjusted according to different performance control requirements. In specific implementation, the aforementioned importance degree and the corresponding relative importance parameter can be obtained by using empirical methods or training a prediction model based on machine learning, neural networks, etc. using a large amount of existing data, and this embodiment is not limited to this.

[0108] Among them, the nth node refers to the last node at the end of the corresponding node sequence. The last node is the least important node for the performance management process in the corresponding node sequence, that is, the node with the smallest weight coefficient in the node sequence. Starting the calculation from the node with the smallest weight coefficient can avoid frequent adjustments to the weight value in subsequent calculations, thereby simplifying the calculation process to reduce the computing burden of the server. It is understandable that in some other embodiments, when the order of the node sequence is different, the selected node may also be the first or other node, as long as its weight coefficient is the smallest. Of course, in some scenarios where the computing burden does not need to be considered, other nodes such as the node with the largest weight coefficient can also be selected to start the calculation.

[0109] Among them, the weight coefficient of the last node (i.e., the nth node) is determined by the following formula:

[0110]

[0111] Among them, r z is the zth relative importance parameter.

[0112] Among them, the weight coefficient of the n-1th node is determined by the following formula:

[0113] w n-1 =r n × n (2)

[0114] Among them, w n-1 is the indicator weight coefficient of the n-1th performance evaluation indicator, r n is the relative importance parameter between the nth performance evaluation indicator and the n-1th performance evaluation indicator.

[0115] Exemplarily, based on the node sequence, the server determines the node with the smallest weight coefficient in the node sequence, that is, the nth node, and uses the above formula (1) to calculate the weight coefficient of the nth node; then, the server obtains the relative importance parameter between the nth node and the n-1th node, and uses the above formula (2) to calculate the weight coefficient of the n-1th node based on the relative importance parameter between the nth node and the n-1th node and the weight coefficient of the nth node, and repeats the above process until the weight coefficient of each node is obtained.

[0116] In this embodiment, different node types are sorted according to their respective importance levels, and weight coefficients are determined based on the relative importance parameters of each node in the corresponding sequence. The relative importance is determined by comparison between nodes. The results have good consistency and there is no need to construct a judgment matrix and perform consistency checks. This ensures that the comprehensive weight coefficient is accurate and objective while improving the determination efficiency.

[0117] In one embodiment, the performance scores of the child nodes are obtained, and the performance scores of the intermediate nodes and the total performance scores of the performance nodes are determined step by step based on the performance scores of the child nodes, the weight coefficients of the child nodes, and the weight coefficients of the intermediate nodes, to obtain the performance evaluation results of the project, including:

[0118] Obtain the first performance score of each measure node, and determine the second performance score of each element node based on the first performance score and the first weight coefficient; determine the third performance score of each system node based on the second performance score and the second weight coefficient; determine the total performance score of the performance node based on the third performance score and the third weight coefficient and the fourth weight coefficient to obtain the performance evaluation result of the project.

[0119] Among them, the second and third performance scores are determined using the following formula:

[0120]

[0121] Among them, A k is the performance score of the corresponding node in the kth level. In this embodiment, k=2,3. In other embodiments with multiple layers of intermediate nodes, k=2,3,...K, where K is the number of layers of intermediate nodes. is the mth in the k-1th level k The weight coefficient of a node relative to its parent node, such as a1 is the first weight coefficient of the child node to the intermediate node of the parent. is the mth in the k-1th level k The performance score of each node, such as p1 is the first performance score, m k =1,2,...,M k , M k is the number of lower-level nodes corresponding to the previous node in the k-th level.

[0122] The total performance score is determined using the following formula:

[0123]

[0124] Among them, PM is the total performance score, w i is the third weight coefficient of the i-th disordered node relative to the performance node, f i is the performance score of the i-th unordered node, i=1,2,...I, I is the number of unordered nodes, v ij is the fourth weight coefficient of the jth ordered node relative to the ith unordered node, and the gth j is the performance score of the jth ordered node, j = 1, 2, ..., J, and J is the number of ordered nodes.

[0125] Exemplarily, the server obtains the first performance score of each measure node, and based on the first performance score and the first weight coefficient, determines the second performance score of each element node using the above formula (3); based on the second performance score and the second weight coefficient, determines the third performance score of each system node using the above formula (3); and based on the third performance score and the third weight coefficient, the fourth weight coefficient and using the above formula (4), determines the total performance score of the performance node.

[0126] In this embodiment, the performance scores corresponding to the nodes at each level are transmitted step by step based on the weight coefficients of the nodes at each level, which can quantify the performance control process and obtain the performance score of the performance control process of the target project, which is conducive to objectively and accurately grasping the performance management process of the target project.

[0127] In an application example, a project performance control method based on a complex network is provided, and a pumped storage power station project in a certain place is taken as a target project to specifically illustrate the project performance control method based on a complex network in this example.

[0128] Complex network is a method of abstracting and modeling complex systems based on graph theory. The elements in the system are represented by nodes in the complex network, and the relationship between the elements can be represented by the edges between the nodes. When this method is applied to the performance management of engineering systems, the complex relationship between the decomposed subsystems and the overall performance of the project can be drawn into a system performance network in the form of a network diagram. On this basis, by calculating the statistical indicators of the network and analyzing the characteristics of the network, the internal mechanism and potential laws of the engineering performance management system can be revealed, thereby assisting in finding the key element nodes and key influencing paths in the system.

[0129] Since the pumped storage power station engineering system is an invisible network, the following construction principles are proposed to establish a more intuitive safety management topology model:

[0130] (1) The pumped-storage power station engineering system is a series system, that is, if any of the nine subsystems fails, the pumped-storage power station engineering system will collapse. The reliability of the nine subsystems jointly determines the reliability of the pumped-storage power station engineering system.

[0131] (2) In the subsystem model, the interaction between elements can be described by control subtrees (divided into two types: sequential subtrees and non-sequential subtrees), such as Figure 4As shown in the figure. The sequential subtree is characterized by the sequential occurrence of subsequent behaviors after the previous behavior ends. There is a sequence of occurrence of element behaviors, which is represented by “→” in the model. A1, A2, and A3 are the next-level elements of A, and A1, A2, and A3 occur in sequence. The reliability probability of A is the product of the reliability probabilities of A1, A2, and A3. The non-sequential subtree is characterized by the fact that there is no sequence of occurrence of element behaviors, and the system security is jointly guaranteed. It is represented by “—” in the model. B1, B2, and B3 are the next-level elements of B, and B1, B2, and B3 can occur at the same time. The reliability probability of B is obtained by summing the reliability probabilities of B1, B2, and B3 according to the weights.

[0132] (3) Since the elements are virtually connected, all edges in the network are simplified to undirected and unweighted edges.

[0133] According to the above principles, the complex network models of each subsystem are established as follows: Figure 5 As shown in the figure, the overall performance of the pumped storage power station system is directly affected by the multi-objective control dimension group (i.e., the four target subsystems of quality management, safety and health, progress management, and investment management), while the remaining five secondary subsystems (i.e., structural decomposition, construction procedures, organization, resources, and technology subsystems) will directly affect the four targets and thus indirectly affect the overall performance of the system. Each subsystem is divided into multiple management elements and each management element is divided into multiple management measures (e.g., Figure 6 The system network diagram of the construction program subsystem is shown. The system network diagrams of other subsystems are similar and will not be repeated in this example).

[0134] Based on the construction of a complex network model associated with each subsystem element, the complex network can be used for further analysis. The subsystem score is determined by the group element. The group is decomposed into measures, and the weights of each measure are transferred by assigning values ​​to the measures, and the weighted sum is used to obtain the score of each group. Taking the structural subsystem under the quality goal as an example, the structural subsystem includes five groups of elements: engineering structure decomposition, organizational structure decomposition, work task decomposition, cost structure decomposition, and risk factor decomposition, including 16 specific measure elements.

[0135] The influence transfer from measures to groups. Pumped storage power stations are scored from the measure dimension, and the structural decomposition subsystem is ranked. Six measures affect five groups of factors, of which five measures in the EBS (Enterprise Breakdown Structure) group are supporting projects, plant systems, water delivery systems, upstream reservoirs, and downstream reservoirs, and their weights are recorded as a11, a12, a13, a14, and a15, which are 0.13, 0.23, 0.24, 0.2, and 0.2, respectively. The weights of the two measures in the OBS (Organizational Breakdown Structure) group, division of responsibilities and department settings, are recorded as a21 and a22, which are 0.527 and 0.473, respectively. The two measures in the WBS (Work Breakdown Structure) group are quality management cycle and workflow, and their weights are recorded as a31 and a32, which are 0.548 and 0.452, respectively. The three measures in the cost breakdown structure (CBS) group are decomposition by project, decomposition by time, and decomposition by cost, and their weights are recorded as a41, a42, and a43, which are 0.412, 0.432, and 0.156 respectively. The four measures in the RBS (Resource Breakdown Structure) group are technical risk, economic risk, environmental risk, and social risk, and their weights are recorded as a51, a52, a53, and a54, which are 0.25, 0.15, 0.4, and 0.2 respectively. Group value = ∑ measure value × weight.

[0136] Based on the above, the group values ​​of each group are expressed as:

[0137] P EBS =84×a 11 +86×a 12 +83×a 13 +83×a 14 +82×a 15 =83.62 (5)

[0138] P OBS =84×a 21 +81×a 22 =82.581 (6)

[0139] P WBS =83×a 31 +84×a 32 =83.452 (7)

[0140] P CBS =70×a41 +74×a 42 +76×a 43 =72.664 (8)

[0141] P RBS =81×a 51 +84×a 52 +84×a 53 +85×a 54 =83.45 (9)

[0142] Where P EBS ,P OBS ,P WBS ,P CBS ,P RBS They are the group values ​​of the five groups: EBS, OBS, WBS, CBS, and RBS.

[0143] The influence transfer from group to subsystem. The five groups EBS, OBS, WBS, CBS, and RBS are transferred through the path, and their weights are recorded as a1, a2, a3, a4, and a5, which are 0.25, 0.2, 0.15, 0.2, and 0.2, respectively, so as to obtain the value of the structural subsystem. Subsystem value = ∑ group value × weight.

[0144] Based on the above, the subsystem numerical representation of the structural decomposition subsystem is:

[0145] P 结构 =P EBS ×a1+P OBS ×a2+P WBS ×a3+P CBS ×a4+P RBS ×a5=81.1618 (10)

[0146] Among them, P 结构 Subsystem value for the structural decomposition subsystem.

[0147] The overall performance of the pumped storage power station engineering system depends on the scores of each subsystem, and the scores of each subsystem depend on each group, which can be further refined to the scores of each measure element. After the scores of each subsystem are calculated, the overall performance of each subsystem and the entire system can be quantitatively analyzed based on the two relationships of the subsystem sequential subtree and non-sequential subtree, using the relevant knowledge of probability theory.

[0148] The sequential subtree relationship represents the sequential influence, and the product of the weights of the subordinate indicators is used to obtain the degree of indirect influence on the overall performance. The weight calculation formula for the sequential subtree system with n' elements is:

[0149]

[0150] Among them, P represents the weight product, that is, the degree of influence of indirect effect on total performance; p' i' Represents the weight of the i'th element in the sequential subtree element.

[0151] Non-sequential subtrees represent simultaneous occurrences. In probability theory, the scores of lower-level indicators are summed by weight to obtain the scores of higher-level indicators. The score calculation formula for a non-sequential subtree system with n" elements is:

[0152]

[0153] In the formula, A represents the superior score, a i” Represents the weight of the "i"th element in the non-sequential subtree.

[0154] Finally, the total performance PM of the system is calculated using formula (13):

[0155]

[0156] Among them, PM is the total performance score, w i is the third weight coefficient of the i-th disordered node relative to the performance node, f i is the performance score of the i-th unordered node, i = 1, 2, 3, 4, I is the number of unordered nodes, v ij is the fourth weight coefficient of the jth ordered node relative to the ith unordered node, and the gth j is the performance score of the jth ordered node, j = 1, 2, 3, 4, 5, and J is the number of ordered nodes.

[0157] Taking the target "quality management" as an example to explain the network diagram, the score of the "quality management" subsystem has been calculated based on the performance score of each group and each element of each subsystem, which is recorded as f1. "Quality management" and the five sub-subsystems form a non-sequential subtree structure, which can be obtained by formula (21) based on the scores of the five sub-subsystems. Since the five subsystems have an indirect effect on the overall performance of the system, according to the idea of ​​sequential subtree, the scores need to be Multiplying by the weight w1 of the "quality management" subsystem completes the upward transfer, and finally the total performance of the clear storage power station system is calculated to be 84.3239.

[0158] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0159] Based on the same inventive concept, the embodiment of the present application also provides a performance control device for implementing the performance control method of the project involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the performance control device embodiment of one or more projects provided below can refer to the limitations of the performance control method of the project above, and will not be repeated here.

[0160] In an exemplary embodiment, Figure 7 As shown, a project performance control device is provided, including: a model building module 701, a weight coefficient determination module 702 and a performance score output module 703, wherein:

[0161] A model building module 701 is used to build a performance control model for a target project; the performance control model has a performance node set based on the target project, multiple levels of intermediate nodes set step by step from the performance node, and multiple sub-nodes set from the terminal intermediate node;

[0162] The weight coefficient determination module 702 is used to determine the weight coefficient of each node at the same level in the corresponding upper level intermediate node or performance node;

[0163] The performance score output module 703 is used to obtain the performance score of the child node, and determine the performance score of the intermediate node and the total performance score of the performance node step by step based on the performance score of the child node, the weight coefficient of the child node and the weight coefficient of the intermediate node, so as to perform performance management and control on the target project based on the total performance score.

[0164] In an optional embodiment, the intermediate node includes at least a plurality of parallel system nodes and a plurality of parallel element nodes arranged downward from each system node, each element node is provided with a plurality of parallel child nodes, and the child nodes are defined as measure nodes.

[0165] The model construction module 701 is also used to set performance nodes based on the target project; divide the target project into multiple project management subsystems according to the horizontal dimension, and construct a corresponding system node for each project management subsystem, point the system node to the performance node, and build a performance network between the system node and the performance node; divide the project management subsystem into multiple performance management elements according to project management elements, and construct a corresponding element node for each performance management element, connect the element node with the corresponding system node, and build a performance network between the element node and the system node; divide the performance management elements into multiple management measures according to project management measures, and construct a corresponding measure node for each management measure, connect the measure node with the corresponding element node, and build a performance network between the measure node and the element node; based on the performance network between each node, a performance control model of the pumped storage power station is constructed.

[0166] In an optional embodiment, the model building module 701 is also used to determine the system nodes as ordered nodes or unordered nodes according to the influence relationship between the system nodes corresponding to each project management subsystem and the performance nodes; the unordered nodes directly affect the performance nodes, and the ordered nodes indirectly affect the performance nodes through the corresponding unordered nodes; each ordered node is pointed to each unordered node, and each unordered node is pointed to the performance node, so as to construct a performance network between the system nodes and the performance nodes.

[0167] In an optional embodiment, the weight coefficient determination module 702 is also used to determine a first weight coefficient of the importance of each measure node corresponding to the same element node in the corresponding element node according to the preset importance of each measure node relative to the corresponding element node; determine a second weight coefficient of the importance of each element node corresponding to the same system node in the corresponding system node according to the preset importance of each element node relative to the corresponding system node; determine a third weight coefficient of the importance of each unordered node corresponding to the performance node in the performance node according to the preset importance of each unordered node relative to the performance node; and determine a fourth weight coefficient of the importance of each ordered node corresponding to the same unordered node in the corresponding unordered node according to the preset importance of each ordered node relative to each unordered node.

[0168] In an optional embodiment, the weight coefficient determination module 702 is also used to determine a node sequence; the node sequence is an unordered node sequence obtained by sorting each unordered node from large to small according to a preset importance in a performance node, an ordered node sequence obtained by sorting each ordered node according to a preset importance in a corresponding unordered node, an element node sequence obtained by sorting each element node from large to small according to a preset importance in a corresponding system node, and / or a measure node sequence obtained by sorting each measure node from large to small according to a preset importance in a corresponding element node; based on the node sequence, determine the weight coefficient of the nth node in the node sequence; the nth node is the last node in the node sequence; obtain the relative importance parameter between the nth node and the n-1th node; the relative importance parameter is determined based on the relative importance between two adjacent nodes; determine the weight coefficient of the n-1th node based on the relative importance parameter between the nth node and the n-1th node and the weight coefficient of the nth node, and repeat this cycle until the weight coefficient of each node is obtained.

[0169] In an optional embodiment, the performance score output module 703 is also used to obtain the first performance score of each measure node, determine the second performance score of each element node based on the first performance score and the first weight coefficient; determine the third performance score of each system node based on the second performance score and the second weight coefficient; determine the total performance score of the performance node based on the third performance score and the third weight coefficient and the fourth weight coefficient.

[0170] Each module in the performance control device of the above project can be implemented in whole or in part by software, hardware and their combination. Each module can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each module above.

[0171] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 8As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as the weight coefficient and performance score of the node. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a performance control method for a project is implemented.

[0172] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0173] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the performance management method of the project of the above embodiment is implemented.

[0174] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the performance management method of the project in the above embodiment is implemented.

[0175] In one embodiment, a computer program product is provided, including a computer program, which implements the performance management method of the project of the above embodiment when executed by a processor.

[0176] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0177] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0178] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0179] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A performance control method for a project, characterized in that: The method comprises: Construct a performance control model for the target project; the performance control model has a performance node set based on the target project, a multi-level intermediate node set step by step from the performance node, and a plurality of sub-nodes set from the terminal intermediate node; the intermediate node at least includes a plurality of parallel system nodes and a plurality of parallel element nodes set downward from each system node, each element node is provided with a plurality of parallel sub-nodes, and the sub-nodes are defined as measure nodes, the target project has a project management subsystem divided according to the horizontal dimension of performance control and corresponding one-to-one with the system nodes, each of the management subsystems has a plurality of management elements divided according to project management elements and corresponding one-to-one with the element nodes, and each of the management elements has a plurality of management measures divided according to project management measures and corresponding one-to-one with the measure nodes; Determine the weight coefficient of each node at the same level in the corresponding intermediate node or performance node at the previous level; the weight coefficient is used to indicate the importance of each node at each level in the corresponding intermediate node or performance node at the previous level for performance control; Obtain the performance score of the child node, determine the performance score of the intermediate node step by step based on the performance score of the child node and the weight coefficient of the child node, and determine the total performance score of the performance node based on the performance score of the intermediate node below the performance node and the weight coefficient corresponding to the intermediate node, so as to perform performance control on the target project based on the total performance score.

2. The method according to claim 1, characterized in that The construction of the performance control model of the target project includes: Setting the performance node based on the target project; Divide the target project into multiple project management subsystems according to the horizontal dimension of performance control, construct a corresponding system node for each project management subsystem, point the system node to the performance node, and construct a performance network between the system node and the performance node; Dividing the project management subsystem into a plurality of performance management elements according to project management elements, constructing a corresponding element node for each performance management element, connecting the element node with a corresponding system node, and constructing a performance network between the element node and the system node; Divide the performance management elements into multiple management measures according to project management measures, construct corresponding measure nodes for each management measure, connect the measure nodes with corresponding element nodes, and construct a performance network between the measure nodes and the element nodes; Based on the performance network between nodes, a performance management and control model is constructed.

3. The method according to claim 2, characterized in that The step of directing the system node to the performance node and constructing a performance network between the system node and the performance node includes: According to the influence relationship between the system nodes corresponding to each project management subsystem and the performance node, the system node is determined as an ordered node or an unordered node; the unordered node directly affects the performance node, and the ordered node indirectly affects the performance node through the corresponding unordered node; Each ordered node is pointed to each unordered node, and each unordered node is pointed to the performance node, so as to construct a performance network between the system node and the performance node.

4. The method according to claim 3, characterized in that The step of respectively determining the weight coefficient of each node at the same level in the corresponding intermediate node or performance node at the previous level includes: Determine a first weight coefficient of the importance of each measure node corresponding to the same element node in the corresponding element node according to the preset importance of each measure node relative to the corresponding element node; Determining a second weight coefficient of importance of each element node corresponding to the same system node in the corresponding system node according to the preset importance of each element node relative to the corresponding system node; Determining a third weight coefficient of the importance of each unordered node corresponding to the performance node in the performance node according to the preset importance of each unordered node relative to the performance node; According to the preset importance of each ordered node relative to each unordered node, a fourth weight coefficient of the importance of each ordered node corresponding to the same unordered node in the corresponding unordered node is determined.

5. The method according to claim 4, characterized in that The first to fourth weight coefficients are determined by the following method: Determine a node sequence; the node sequence is an unordered node sequence obtained by sorting the unordered nodes in descending order according to the preset importance in the performance node, an ordered node sequence obtained by sorting the ordered nodes in the corresponding unordered nodes according to the preset importance in the corresponding system node, an element node sequence obtained by sorting the element nodes in descending order according to the preset importance in the corresponding system node, and / or a measure node sequence obtained by sorting the measure nodes in descending order according to the preset importance in the corresponding element node; Based on the node sequence, determining a weight coefficient of an nth node in the node sequence; the nth node is the last node in the node sequence; Obtaining a relative importance parameter between the nth node and the n-1th node; the relative importance parameter is determined according to the relative importance between two adjacent nodes; The weight coefficient of the n-1th node is determined according to the relative importance parameter between the n-th node and the n-1-th node and the weight coefficient of the n-th node, and this cycle is repeated until the weight coefficient of each node is obtained.

6. The method according to claim 4, characterized in that The obtaining of the performance score of the child node, and determining the performance score of the intermediate node and the total performance score of the performance node step by step based on the performance score of the child node, the weight coefficient of the child node and the weight coefficient of the intermediate node, includes: Obtain a first performance score for each measure node, and determine a second performance score for each element node based on the first performance score and the first weight coefficient; determine a third performance score for each system node based on the second performance score and the second weight coefficient; and determine an overall performance score for the performance node based on the third performance score and the third and fourth weight coefficients.

7. A project performance control device, characterized in that: The device comprises: A model building module, used to build a performance control model for a target project; the performance control model has a performance node set based on the target project, multiple levels of intermediate nodes set step by step from the performance node, and multiple sub-nodes set from the terminal intermediate node; A weight coefficient determination module is used to determine the weight coefficient of each node at the same level in the corresponding intermediate node or performance node at the previous level; A performance score output module is used to obtain the performance score of the child node, and determine the performance score of the intermediate node and the total performance score of the performance node step by step based on the performance score of the child node, the weight coefficient of the child node and the weight coefficient of the intermediate node, so as to perform performance management of the target project based on the total performance score.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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